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filipposML t1_jamongz wrote

Reply to comment by M_Alani in [D] Are Genetic Algorithms Dead? by TobusFire

We recently published an evolutionary method to sample from the latent space of a variational autoencoder. It is still alive and well. Just a bit niche.

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mmmniple t1_jan7i1a wrote

It sounds very interesting. Is it available to read? Thanks

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avialex t1_janjx6r wrote

Appears to be here: https://openreview.net/forum?id=ibNr25jJrf

edit: actually after reading it, I don't think this is the referenced publication, but it's still interesting

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filipposML t1_jaooo3f wrote

Hey, this is it actually! We are optimizing a discrete variational autoencoder with no gumbel-softmax trick.

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filipposML t1_jaop5vw wrote

Of course we require no encoding model, so the notion of a latent space only holds up until closer inspection.

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avialex t1_jap04wq wrote

I was kinda excited, I had hoped to find an evolutionary algorithm to find things in a latent space, I've been having a hell of a time trying to optimize text encodings for diffusion models.

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filipposML t1_jaq6tpq wrote

You just need a notion of a fitness function and then you can apply permutations to the tokens.

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